东北大学学报:自然科学版 ›› 2019, Vol. 40 ›› Issue (2): 153-158.DOI: 10.12068/j.issn.1005-3026.2019.02.001

• 信息与控制 •    下一篇

动态火焰图像分割及在电熔镁炉视频监控中的应用

卢绍文, 李鹏琦, 郑秀萍, 郭章   

  1. (东北大学 流程工业综合自动化国家重点实验室, 辽宁 沈阳110819)
  • 收稿日期:2017-12-10 修回日期:2017-12-10 出版日期:2019-02-15 发布日期:2019-02-12
  • 通讯作者: 卢绍文
  • 作者简介:卢绍文(1977-), 男, 河北保定人, 东北大学教授; 郑秀萍(1966-),女, 辽宁沈阳人,东北大学教授.
  • 基金资助:
    国家自然科学基金资助项目(61473071,61833004); 辽宁省教育厅重点实验室基础研究项目(LZ2015033).

A Dynamic Flame Image Segmentation Method and Its Application in Video Monitoring of Fused Magnesium Furnace Process

LU Shao-wen, LI Peng-qi, ZHENG Xiu-ping, GUO Zhang   

  1. State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang 110819, China.
  • Received:2017-12-10 Revised:2017-12-10 Online:2019-02-15 Published:2019-02-12
  • Contact: LU Shao-wen
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摘要: 火焰的颜色、亮度分布、形态变化规律在不同工况下均不相同,表现出多模态的特点;此外,背景环境的反光、气雾、粉尘等干扰使得目标区域和背景高度耦合,因此传统分割算法不能确保在多种工况下的准确性.本文提出将多元图像分析和人工经验相结合的火焰图像分割方法,通过主成分分析方法对图像降维、构造得分柱状图,进而分割出炉口火焰区域.将本文方法应用于电熔镁炉生产的视频监控中,结果验证了该方法的性能.

关键词: 图像分割, 动态火焰, 多元图像分析, 电熔镁炉, 视频监控

Abstract: The color, brightness distribution and shape pattern of flames vary under different working conditions, thus showing multi-modality. In addition, the background environment is highly coupled with the foreground image because of the reflection, aerosol, dust and other interferences. Traditional segmentation algorithms cannot ensure accuracy under a variety of conditions. A method of flame image segmentation based on multivariate image analysis and expert knowledge is proposed. The principal component analysis method was used to reduce the dimension of images and to construct the scatter plot of the scores, so as to obtain the regions of flame segmentation. The method was applied to the video monitoring of the production of fused magnesium furnace, which verified the performance of this method.

Key words: image segmentation, dynamic flame, multivariate image analysis, fused magnesium furnace process, video monitoring

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